Beiken Energy Group (002828) Fair Value & Analysis
Energy · CN · Market cap 1.8B CNY
Fair value as of: Jun 25, 2026
Analysis
Beiken Energy Group (002828) currently trades at ¥9.91, while our model-based Fair Value estimate is ¥2.91 — implying the stock looks roughly 70.6% overvalued today. We read business quality at 95/100 (high quality), in the Energy sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Beiken Energy Group Co., Ltd., together with its subsidiaries, engages in the oil, gas, and geology businesses in China and internationally. The company offers oil and gas extraction, coal mine de-gas integrated, and coal seam gas engineering services. It also engages in waste gas and coal slag deep processing, and air product processing services; and provides oil field chemical products, and other technical services, as well as engages in trading of chemical materials, oil field equipment, spares, and other energy related products. In addition, the company is involved in geomodelling design, development plan design, surface construction drilling, cement and mud logging, and wireline logging, as well as offer oil and gas maintenance services. Further, it provides financing services for engineering business. The company was formerly known as XinJiang Beiken Energy Engineering Co.,Ltd. and changed its name to Beiken Energy Group Co., Ltd. in September 2024. Beiken Energy Group Co., Lt…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.